Increasingly stringent Federal regulations directed to protecting workers and the environment require industry businesses to employ "best" maintenance practices. An example of such a Federal Regulation is the OSHA rule on Process Safety Management of Highly Hazardous Chemicals (29 CFR Ch. XVII 1910.119). Best maintenance practice increasingly include predictive maintenance to monitor vibration and other physical variables for forecasting machine failures. Gathering and maintaining complete records to comply with such regulations is not provided for in an efficient and economic fashion by conventional monitoring technology.
One conventional predictive maintenance system is described in U.S. Pat. No. 4,885,707 in which a portable data logger is used to measure vibration of machinery. The vibration is sensed by electromechanical transducers temporarily attached by an operator to permanent indexing mounts at each test station. Devices of this type do not automatically collect data on a specified schedule, are generally cumbersome to operate, have limited technical capabilities and are expensive to manufacture. The shortcomings of such devices result in limiting the frequency of data monitoring.
The use of portable data loggers is typically insufficient in satisfying government regulations. For example, human error of an analyst using the data logger such as being absent or forgetting can result in gaps in the data record. One conventional solution has been to employ centralized on-line systems connected to host computers to provide continuous records of the monitored apparatus. Conventional on-line systems have the drawback of having high data storage requirements resulting in high purchase costs.
U.S. Pat. No. 4,931,949 to the assignee of the present disclosure describes a gear defect analyzing system. Signals from a gear box are detected by an accelerometer and a shift encoder and fed to an analog pre-processing circuit. The pre-processor conditions the signal so it can be analyzed by a microcomputer. The system is capable of detecting, classifying and analyzing hard-to-find defects.
U.S. Pat. No. 5,305,295 relates to efficient data storage by matching compressed data records to sectors or blocks of appropriate known sizes. While this system achieves efficient utilization of space in memory, it assumes that all data are of equal value. In machine sensing differences in value can exist among individual records, making adaptive data compression desirable.
U.S. Pat. No. 5,249,053 describes variable data compression to achieve maximum image quality for filmless pictures stored in fixed size memory blocks. This device has the limitation that balancing maximum image quality with memory restrictions for a single data record at the time of data acquisition does not take into account the relative values or importance of a series of records or the data therein. The determination of the relative values of a series of data records is advantageous for providing regulatory compliant machine monitoring and providing optimum alarm condition analysis while minimizing system memory requirements.
U.S. Pat. No. 5,243,343 relates to varied time range digitizing as a means of data compression. Memory requirements are minimized by digitizing information after the occurrence of a desired change rate in the data. This invention is not directed to vibration monitoring and has the shortcoming that if the teachings were used in vibration monitoring the method would not form a series of data monitoring records useful in alarm related analysis or regulatory compliance.
U.S. Pat. No. 4,559,828 describes a vibration monitoring system that transmits unprocessed data to a central computer for processing. This invention has the drawback of transmitting large quantities of data to the central computer resulting in an expensive system commercially viable only for critical machinery. The above-described vibration monitoring system is too expensive for many applications.
It is desirable to provide a stand alone monitoring system that can meet the demands of regulatory compliance and can optimally monitor machinery alarm conditions with minimum memory requirements.